Games can be easy to construct but difficult to solve due to current methods available for finding the Nash Equilibrium. This issue is one of many that face modern game theorists and those analysts ...

The adoption of physically simulated character animation in the industry remains a challenging problem, primarily because of the lack of the directability and generalizability of existing methods.

The new framework sidesteps costly and risky real-world rollouts by generating synthetic training data, making powerful ...

For those unfamiliar, Reinforcement Learning (RL) is the science of decision making, specifically referring to how certain behaviors are encouraged, and others discouraged. It is one of three ...

Last week, I wrote an analysis of “Reward Is Enough,” a paper by scientists at DeepMind. As the title suggests, the researchers hypothesize that the right reward is all you need to create the ...

A subset of AI called reinforcement learning is helping scientists improve nuclear fuel technology, which they could use to ...

Strengthening skills: Observational learning is also a key way to reinforce and strengthen behaviors. For example, if a study sees another student getting a reward for raising their hand in class, ...